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ARS Home » Research » Publications at this Location » Publication #121726


item Oscar, Thomas

Submitted to: International Journal of Food Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/10/2002
Publication Date: 6/25/2002
Citation: N/A

Interpretive Summary: Cooked chicken may contain harmful Salmonella bacteria as a result of improper cooking or as a result of improper handling that results in contamination with Salmonella from cutting boards or utensils used to prepare the raw chicken for cooking. Although only a few Salmonella bacteria may be present initially, their numbers can increase quickly when the cooked chicken is held for extended periods of time at temperatures between 43 and 120 F. The actual increase in the number of Salmonella depends on the combined effects of time and temperature. A computer model was developed that predicts the potential increase in the number of Salmonella on cooked chicken as a function of time and temperature (46 to 118 F). In addition, the model predicts how long it takes the Salmonella to start growing and how fast they grow once they start. For example, the model predicts that at 68 F, it will take Salmonella about 4 hours to start growing and that once they start growing their numbers will double every 3.5 hours. The predictions made by the model can be used in a bigger and more complex risk assessment model to predict the relative number of people in a large population that will get ill from chicken that is not properly handled. The risk assessment model is available on the Internet ( as version 2.0 of the Poultry Food Assess Risk Model or Poultry FARM.

Technical Abstract: The growth of Salmonella Typhimurium on the surface of autoclaved ground chicken breast and thigh burgers incubated at constant temperatures from 8 to 48 C in 2 C increments was investigated and modeled. Growth curves at each temperature were fit to a two-phase linear primary model to determine lag time and specific growth rate. Growth of S. Typhimurium on breast and thigh meat was not different. Consequently, secondary models that predicted lag time and specific growth rate as a function of temperature were developed with the combined data for breast and thigh meat. Five secondary models for lag time and three secondary models for specific growth rate were compared. A new version of the hyperbola model and a cardinal temperature model were selected as the best secondary models for lag time and specific growth rate, respectively. The secondary models were combined in a computer spreadsheet to create a tertiary simulation model that predicted the potential growth (log10 increase) of S. Typhimurium on cooked chicken as a function of time and temperature. Probabililty distributions were used in the tertiary model to model the variability and uncertainty of the secondary model parameters and the times and temperatures of abuse. The outputs of the tertiary model were validated and integrated with a previously developed risk asessment model for Salmonella to continue the process of developing an objective process risk model for assessing the microbiological safety of chicken.